A Self -Adaptive Hybrid Genetic Algorithm for Optimal Groundwater Remediation Design
Espinoza, Felipe Patricio
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https://hdl.handle.net/2142/83212
Description
Title
A Self -Adaptive Hybrid Genetic Algorithm for Optimal Groundwater Remediation Design
Author(s)
Espinoza, Felipe Patricio
Issue Date
2003
Doctoral Committee Chair(s)
Minsker, Barbara S.
Department of Study
Civl and Environmental Engineering
Discipline
Civl and Environmental Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Environmental Sciences
Language
eng
Abstract
The application of the e-SAHGA algorithm to a hypothetical groundwater remediation design problem showed 90% reliability in identifying the solution faster than the SGA, with average savings of 64% across 100 runs with different random initial populations. Finally, e-SAHGA was tested on a field-scale remediation design problem, re-evaluation of the remediation system for Umatilla Army Depot, where it gave computational savings between 30% and 60% and, for one solution method, found a solution that was 4% better than the one found by the SGA.
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